空间数据融合的框架流程及发展现状研究

在介绍空间数据概念和框架流程的基础上,文章将数据集成、数据匹配和数据融合三个重要环节分别展开,列举了各自的内容、处理方法及研究现状。重点介绍了基于本体的语义集成,线状、面状要素的数据匹配,矢量、栅格数据间的融合处理,以及空间数据基础设施(SDI)。     

SAR影像与TM影像的几种融合处理方法

利用彩色空间变换、比值变换及相关系数法分别对SAR影像与TM3 、TM4 、TM5 三波段影像进行融合处理。文章介绍了影像融合中的具体技术问题及其处理方法。因侧视雷达图像一般有明显的孤立噪声,所以,在进行影像融合处理之前,先对SAR影像进行预处理,文中用δ滤波法抑制孤立噪声(光斑) .最后,从视觉效果、熵、平均梯度值以及标准差等4 方面评价了影像融合的质量。     

Fusion of PolSAR and PolInSAR data for land cover classification

The main research goal of this study is to investigate the complementarity and fusion of different frequencies (L- and P-band), polarimetric SAR (PolSAR) and polarimetric interferometric (PolInSAR) data for land cover classification. A large feature set was derived from each of these four modalities and a two-level fusion method was developed: Logistic regression (LR) as ‘feature-level fusion’ and the neural-network (NN) method for higher level fusion. For comparison, a support vector machine (SVM) was also applied. NN and SVM were applied on various combinations of the feature sets.     

国家地震烈度速报与预警工程融合决策平台建设

为满足国家地震烈度速报与预警工程(以下简称“国家预警工程”)紧急地震信息对外服务要求,针对国家预警工程建设多算法多中心融合决策的主要技术难题,结合地震监测学科的技术发展现状和学科管理需求,地震监测预警业务系统迫切需要一个用于地震预警、参数速报和烈度速报分系统产出一套全国统一结果的融合决策平台。在国家预警工程定制软件项目实施过程中,建设了国家地震烈度速报与预警工程融合决策平台,其作为国家预警工程数据处理系统与紧急地震信息服务系统之间的关键信息通道,负责汇集融合国、省两级多中心地震预警和速报分系统的多套处理算法的处理结果,进行多个处理结果的同一地震事件判断及其可靠性判定,基于多个策略的信息优选和融合决策处理,产出融合决策后唯一、可靠、及时和准确的预警和速报信息结果。该结果经紧急地震信息服务系统的发布平台对外发布,社会公众、政府机构和特定专业用户可以基于收到的地震预警和速报信息进行防灾避险或应急救援。     

基于多源数据融合的典型海岛三维形貌表征方法研究

随着海岛开发利用和基础设施建设的频繁,高效、精准地获取海岛形态基础数据就显得尤为迫切。三维地形地貌探测和构建技术的日臻完善,及时解决了海岛基础勘测时间长、效率低、精度小的问题。文章通过三维激光扫描和无人机航测手段,全覆盖扫描广西小庙墩(炮台口)海岛表面形态,结合RTK-DGPS实测验证和近景摄影测量,获取海岛实景,运用Geomagic Studio和Smart3D等软件,构建典型海岛三维数字高程模型(DEM),融合多源数据和海岛实景,还原海岛高精度仿真三维形态。为高精度勘测海岛提供有效手段,为海岛基础地理信息获取、地质灾害识别和生态环境修复提供基础数据支撑。     

Toward reduction of artifacts in fused images

Most fusion satellite image methodologies at pixel-level introduce false spatial details, i.e. artifacts, in the resulting fused images. In many cases, these artifacts appears because image fusion methods do not consider the differences in roughness or textural characteristics between different land covers. They only consider the digital values associated with single pixels. This effect increases as the spatial resolution image increases. To minimize this problem, we propose a new paradigm based on local measurements of the fractal dimension (FD). Fractal dimension maps (FDMs) are generated for each of the source images (panchromatic and each band of the multi-spectral images) with the box-counting algorithm and by applying a windowing process. The average of source image FDMs, previously indexed between 0 and 1, has been used for discrimination of different land covers present in satellite images. This paradigm has been applied through the fusion methodology based on the discrete wavelet transform (DWT), using the à trous algorithm (WAT). Two different scenes registered by optical sensors on board FORMOSAT-2 and IKONOS satellites were used to study the behaviour of the proposed methodology. The implementation of this approach, using the WAT method, allows adapting the fusion process to the roughness and shape of the regions present in the image to be fused. This improves the quality of the fused images and their classification results when compared with the original WAT method.     

一种DLG数据要素融合算法的设计与实现

空间数据生产是分幅进行的,因此,在实际应用中经常需要将跨图幅的面状或线状要素,合并成同一要素,使其符合现实世界情况.从数据生产与应用的角度,提出了一种DLG数据要素融合算法,并基于.net平台使用C#语言对算法进行了实现.实践证明,该算法对DLG数据要素融合是有效的,且算法处理效率较高.     

Partial iterates for symmetrizing non-parametric color correction

Mosaic generation is a central tool in various fields ranging way beyond the scope of photogrammetry and requires the radiometry and color of the images to be corrected. Correction can either be done by a global parametric approach (looking for an optimal gain or gamma for each image of the mosaic), or by iteratively correcting image pairs with a non-parametric approach. Such non-parametric approaches allow for much finer correction but are asymmetric, i.e. they require the choice of a source image that will be corrected to match a target image. Thus the result on the whole mosaic will be very dependant on the order in which images are corrected. In this paper, we propose to use partial iterates to symmetrize non-parametric correction in order to solve this problem. Partial iterates formalize what partially applying a bijective function means and we explain how this can be done in both the continuous and discrete domain. This mechanism is applied to a simple non-parametric approach (histogram transfer of the luminance) to show its potential.     

Earth observation data based rapid flood-extent modelling for tsunami-devastated coastal areas

Earth observation (EO)-based mapping and analysis of natural hazards plays a critical role in various aspects of post-disaster aid management. Spatial very high-resolution Earth observation data provide important information for managing post-tsunami activities on devastated land and monitoring re-cultivation and reconstruction. The automatic and fast use of high-resolution EO data for rapid mapping is, however, complicated by high spectral variability in densely populated urban areas and unpredictable textural and spectral land-surface changes. The present paper presents the results of the SENDAI project, which developed an automatic post-tsunami flood-extent modelling concept using RapidEye multispectral satellite data and ASTER Global Digital Elevation Model Version 2 (GDEM V2) data of the eastern coast of Japan (captured after the Tohoku earthquake). In this paper, the authors developed both a bathtub-modelling approach and a cost-distance approach, and integrated the roughness parameters of different land-use types to increase the accuracy of flood-extent modelling. Overall, the accuracy of the developed models reached 87–92%, depending on the analysed test site. The flood-modelling approach was explained and results were compared with published approaches. We came to the conclusion that the cost-factor-based approach reaches accuracy comparable to published results from hydrological modelling. However the proposed cost-factor approach is based on a much simpler dataset, which is available globally.     

Multi—beam Sonar and Side—scan Sonar Image Co—registering and Fusing

Multi-beam Sonar and Side-scan Sonar compensate each other.In order to fully utilize all information,it is necessary to fuse two kinds of image and data.And the image co-registration is an important and complicated job before fusion.This paper suggests combining bathymetric data with intensity image,obtaining the characteristic points through the minimal angles of lines,and then deciding the corresponding image points by the maximal correlate coefficient in searching space.Finally,the second order polynomial is applied to the deformation model.After the images have been co-registered,Wavelet is used to fuse the images.it is shown that this algorthm can be used in the flat seafloor or the isotropic seabed.Verification is made in the paper with the observed data.